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Earth Engine, ENVI, MATLAB, or R. Desirable Proficiency in applying machine learning methods to multispectral and hyperspectral data for detecting crop diseases and estimating crop yield and quality
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. Good knowledge of the topic of Cryospheric Processes is a requirement Proficiency in scientific coding and data analysis programming languages, such as Python or MATLAB, is a requirement. Experience with
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on the development of optical models, image acquisition software, image processing algorithms, and deep learning algorithms using Zemax, Python, Matlab, LabVIEW, CUDA, and other programming environments. Training
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have until 30.06.2026 to complete the final exam. Desired / Beneficial qualifications: Valid driver’s license. Programming and numerical analysis skills (e.g., Python, MATLAB) and/or experience with
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. Minimum two (2) years of experience with programming language (e.g. Matlab, R or Python) and statistics. Desired Qualifications* Minimum two (2) years of experience to learn systems biology approaches, high
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programming skills in at least one of the following (Python, MATLAB, Julia). Please ensure you read the Job Description and Person Specification for full details of this role, by clicking the 'Apply' button
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photonic design Proficiency in Ansys Lumerical, Tidy3D, Python, MATLAB, and GDSfactory Strong written and oral communication skills Ability to work independently under strict timelines with excellent
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. Proficiency in data analysis software (e.g., R, MATLAB, SPSS, Primer, Python). Experience with analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem
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., Python, Matlab, R). You must meet the requirements for admission to a postdoctoral program at the Faculty of Medicine and Health Sciences. At least one first (or co-first) author publication in high-impact
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, including stringent controls, method validation, and troubleshooting in high-variability biological samples. Strong quantitative competence and programming experience (Python and/or R/Matlab) for reproducible